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Risk Spillover between Shipping Company's Stock Price and Marine Freight Index

해운선사 주가와 해상운임지수 사이의 위험 전이효과

  • 최기홍 (부산대학교 경제통상연구원)
  • Received : 2023.02.28
  • Accepted : 2023.03.31
  • Published : 2023.03.31

Abstract

This study analyzed the risk spillover of BDI on shipping company stock prices through the Copula-CoVaR method based on daily data from January 4, 2010, to October 31, 2022. The main empirical analysis results and policy implications are as follows. First, copula results showed that there was a weak dependence between BDI and shipping company stock prices, and PAN, KOR, and YEN were selected as the most fitting model for dynamic Student-t copula, HMM was selected as the rotated Gumbel copula, and KSS was selected as the best model. Second, in the results of CoVaR, it was confirmed that the upside (downside) CoVaR was significantly different from the upside (downside) VaR in all shipping companies. This means that BDI has a significant risk spillover on shipping companies. In addition, as for the risk spillover, the downside risk is generally lower than the upside risk, so the downside and upside risk spillover were found to be asymmetrical. Therefore, policymakers should strengthen external risk supervision and establish differentiated policies suitable for domestic conditions to prevent systematic risks from BDI shocks. And investors should reflect external risks from BDI fluctuations in their investment decisions and construct optimal investment portfolios to avoid risks. On the other hand, investors propose that the investment portfolio should be adjusted in consideration of the asymmetric characteristics of up and down risks when making investment decisions.

본 연구는 2010년 1월 4일부터 2022년 10월 31일까지의 일별 자료를 기반으로 Copula-CoVaR 방법을 통해 해운선사 주가에 미치는 BDI의 위험 전이효과를 분석하였다. 주요 실증분석 결과와 정책적 함의는 다음과 같다. 첫째, copula 결과에 따르면, BDI와 해운선사 주가 사이는 약한 의존성이 존재하는 것으로 나타났으며, PAN, KOR, YEN은 동적 Student-t copula가 가장 적합한 모형으로 선정되었으며, HMM은 rotated Gumbel copula, KSS는 Gumbel copula가 선정되었다. 둘째, CoVaR의 결과에서, 모든 해운선사에서 상·하방 CoVaR가 상·하방 VaR과 크게 다르다는 것을 확인하였다. BDI가 해운선사에 상당한 위험 전이효과가 있다는 것을 의미한다. 또한 위험 전이효과는 일반적으로 하방 위험이 상방 위험보다 낮으므로, 하방과 상방 위험 전이효과는 비대칭적인 것으로 나타났다. 따라서 정책입안자들은 BDI 충격으로 인한 체계적인 위험을 방지하기 위해 외부 위험 감독을 강화하고, 국내 여건에 맞는 차별화된 정책을 수립해야한다. 그리고 투자자들은 BDI 변동으로 인한 외부 위험을 투자 결정에 반영하고 위험을 피하기 위해 최적의 투자 포트폴리오를 구성해야 한다. 한편, 투자자들은 투자를 결정할 때 상·하방 위험의 비대칭적 특성을 고려하여 투자 포트폴리오를 조정해야 할 것을 제안한다.

Keywords

References

  1. 김현석.오용식(2012), 해운선사 주가와 운임지수 BDI 변동성간의 관계 분석. 해운물류연구, 제28권 4호, 637-652. https://doi.org/10.37059/TJOSAL.2012.28.4.637
  2. 김형호.성기덕.전준우.여기태(2016), 해운선사 주가와 해상 운임지수의 영향관계 분석. Journal of Digital Convergence, 제14권 6호, 157-165.
  3. 최기홍.김동윤(2019), 발틱운임지수가 한국 주가 변동성에 미치는 영향. 한국항만경제학회지, 제35권 2호, 61-75.
  4. Abadie, A.(2002), Bootstrap tests for distributional treatment effects in instrumental variable models. Journal of the American statistical Association, 97(457), 284-292. https://doi.org/10.1198/016214502753479419
  5. Adrian, T., and Brunnermeier, M. K.(2016), CoVaR. The American Economic Review, 106(7), 1705.
  6. Alizadeh, A. H., and Muradoglu, G.(2014), Stock market efficiency and international shipping-market information. Journal of international financial markets, institutions and money, 33, 445-461. https://doi.org/10.1016/j.intfin.2014.10.002
  7. Bakshi, G., G. Panayotov, and G. Skoulakis(2012), The Baltic Dry Index as a predictor of global stock returns, commodity returns, and global economic activity, In AFA 2012 Chicago Meetings Paper.
  8. Erdogan, O., Tata, K., Karahasan, B. C., and Sengoz, M. H.(2013), Dynamics of the co-movement between stock and maritime markets. International Review of Economics & Finance, 25, 282-290. https://doi.org/10.1016/j.iref.2012.07.007
  9. Giannarakis, G., Lemonakis, C., Sormas, A., and Georganakis, C.(2017), The effect of Baltic Dry Index, gold, oil and usa trade balance on dow jones sustainability index world. International Journal of Economics and Financial Issues, 7(5), 155.
  10. Graham, M., Peltomaki, J., and Piljak, V.(2016), Global economic activity as an explicator of emerging market equity returns. Research in International Business and Finance, 36, 424-435. https://doi.org/10.1016/j.ribaf.2015.09.030
  11. Grammenos, C. T., and Arkoulis, A. G.(2002), Macroeconomic factors and international shipping stock returns. International Journal of Maritime Economics, 4, 81-99. https://doi.org/10.1057/palgrave.ijme.9100033
  12. Lin, A. J., Chang, H. Y., and Hsiao, J. L.(2019), Does the Baltic Dry Index drive volatility spillovers in the commodities, currency, or stock markets?. Transportation Research Part E: Logistics and Transportation Review, 127, 265-283. https://doi.org/10.1016/j.tre.2019.05.013
  13. UNCTAD. "Review of Maritime Transport." In In United Nations Publication, New York and Geneva: United.
  14. Yang, J., Zhang, X., and Ge, Y. E.(2022), Measuring risk spillover effects on dry bulk shipping market: a value-at-risk approach. Maritime Policy & Management, 49(4), 558-576. https://doi.org/10.1080/03088839.2021.1889064